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Dongping Zhang

2 accepted papers

2026

Calibrating Uncertainty for Zero-Shot Adversarial CLIP

ICML 2026poster

CLIP delivers strong zero-shot classification but remains highly vulnerable to adversarial attacks. Prior adversarial fine-tuning work largely focuses on matching the predicted logits between clean and adversarial examples, which overlooks uncertainty calibration and may degrade the zero-shot genera…

Cited by 0SourceScholar
2024

Revisiting the Domain Shift and Sample Uncertainty in Multi-source Active Domain Transfer

CVPR 2024poster

Active Domain Adaptation (ADA) aims to maximally boost model adaptation in a new target domain by actively selecting a limited number of target data to annotate. This setting neglects the more practical scenario where training data are collected from multiple sources. This motivates us to extend ADA…

Cited by 20SourcePDFScholar